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Feature extraction and radar track classification for detecting UAVs in civillian airspace

机译:特征提取和雷达航迹分类,用于检测民用空域中的无人机

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With the rapidly growing use of commercial Unmanned Aerial Vehicles (UAVs), integrating civilian UAVs into the controlled airspace seems inevitable. We investigate the problem of associating correct labels to different radar tracks, specifically to distinguish UAV tracks among others (such as aircraft and birds). To this end, three plausible civilian applications involving UAVs are proposed and studied. Then, for each application, a number of UAV tracks are simulated and merged into an existing dataset of real aircraft and bird tracks. We show that, with a chosen set of track features, the simulated UAV tracks are correctly labeled with 99% accuracy.
机译:随着商用无人飞行器(UAV)的迅速增长,将民用无人机集成到受控空域中似乎是不可避免的。我们研究将正确的标签与不同的雷达航迹相关联的问题,特别是要区分无人机航迹(例如飞机和鸟类)。为此,提出并研究了涉及无人机的三种可能的民用应用。然后,对于每种应用,将模拟许多无人机航迹并将其合并到真实飞机和鸟类航迹的现有数据集中。我们显示,通过选择的一组航迹特征,可以正确地以99%的准确度标记模拟的无人机航迹。

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